Graph Theory with Applications to Engineering and Computer ScienceCourier Dover Publications, 9 ÁÕ.¤. 2017 - 496 ˹éÒ This outstanding introductory treatment of graph theory and its applications has had a long life in the instruction of advanced undergraduates and graduate students in all areas that require knowledge of this subject. The first nine chapters constitute an excellent overall introduction, requiring only some knowledge of set theory and matrix algebra. Topics include paths and circuits, trees and fundamental circuits, planar and dual graphs, vector and matrix representation of graphs, and related subjects. The remaining six chapters are more advanced, covering graph theory algorithms and computer programs, graphs in switching and coding theory, electrical network analysis by graph theory, graph theory in operations research, and more. Instructors may combine these chapters with the preceding material for courses in a variety of fields, including electrical engineering, computer science, operations research, and applied mathematics. |
à¹×éÍËÒ
| 1 | |
PATHS AND CIRCUITS | 14 |
VECTOR SPACES OF A GRAPH | 112 |
MATRIX REPRESENTATION OF GRAPHS | 137 |
COLORING COVERING AND PARTITIONING | 165 |
9 | 194 |
10 | 238 |
11 | 263 |
Shortest Path from a Specified Vertex | 292 |
©ºÑºÍ×è¹æ - ´Ù·Ñé§ËÁ´
Graph Theory with Applications to Engineering and Computer Science Narsingh Deo ªÁºÒ§Êèǹ¢Í§Ë¹Ñ§Ê×Í - 2016 |
¤ÓáÅÐÇÅÕ·Õ辺ºèÍÂ
2-trees activity network acyclic adjacency matrix algorithm analysis applications binary Boolean called Chapter chord circuit matrix cofactor colors column complete graph components connected graph contact network corresponding cut-set matrix digraph G directed circuits directed path edge-disjoint electrical network elements entry equations Euler graph Euler line example fundamental circuit fundamental cut-set G₁ given graph graph G graph in Fig graph theory graph-theoretic Hamiltonian circuit in-degree incidence matrix integer isomorphic labeled linear Markov process max-flow min-cut theorem maximal nonzero nullity number of edges number of vertices obtained out-degree p₁ pair of vertices parallel edges partition permutation planar graph problem program digraph Proof representation represented s₁ self-loop sequential machine shortest shown in Fig signal-flow graph spanning tree stochastic strongly connected subgraph subsets subspace T₁ Theorem topological transport network undirected graph v₁ V₂ variables vector space vertex voltage W₁ weight x₁ zero υς